Computer-assisted stereotactic systems that work with the aid of body structure data obtained from tomographic detection systems and with the assistance of X-ray images produced in situ are known, for example, from U.S. Pat. No. 4,791,934 and U.S. Pat. No. 5,799,055. Furthermore, x-ray imaging used to assist in operations is discussed in U.S. Pat. Nos. 5,967,982; 5,772,594; and 5,784,431.
Where accurate medical navigation is to be provided, the prior art still works with the aid of body structure data originating from tomographic detection systems such as, for example, computer tomography devices or nuclear spin tomography devices. The patient to be treated may be positionally registered in situ with respect to previously determined image data, and operating instruments then may be virtually displayed in the same relation to the image data as to the actual patient. This can make the body structure data and/or X-ray image data useful to the surgeon in the operating room.
A disadvantage of methods in which tomographs (CT, MR) or X-ray images are produced specifically for navigation within the framework of treatment is that it increases a radiation load on the patient. Further, such devices incur high costs, since they are very expensive to purchase and maintain.
Attempts have been made to develop systems that may be employed without using previously detected body structure data, for example, based on statistical models of image data sets for body structures. However, such systems can lack the required accuracy for the respective patient to be treated.
Constructing the bone surface from a few calibrated fluoroscopic images can be a challenging task. A priori information is often required to handle this problem. In Fleute M. and Lavallée S.: Nonrigid 3D/2D registration of images using a statistical model. Lecture Notes in Computer Science, Vol. 1679, Springer (1999) 138-147, a PDM of the distal femur was iteratively fitted to the contours of segmented X-ray views by sequentially optimizing the rigid and non-rigid parameters.
In Benameur S., Mignotte M., Parent S. et al.: 3D/2D registration and segmentation of scoliotic vertebra using statistical models. Comput Med Imag Grap, Vol. 27, (2003) 321-337 and Benameur S., Mignotte M., Parent S., et al.: A hierarchical statistical modeling approach for the unsupervised 3D reconstruction of the scoliotic spine. ICIP '04 (2004), 561-564, a PDM of scoliotic vertebrae was fitted to two conventional radiographic views by simultaneously optimizing both shape and pose parameters. The optimal estimation was obtained by iteratively minimizing a combined energy function, which is the sum of a likelihood energy term measured from an edge potential field on the images and a prior energy term measured from the statistical shape models. No explicit image-to-model correspondence was used. To avoid trapping in a local minimal, the method requires a close initialization.
US 2003/0185346 A1 discloses a method for computer-assisted medical navigation and pre-operative treatment planning, wherein the current position of a patient or a part of a patient's body and the positions of medical treatment devices or treatment-assisting devices are detected by means of a position detection unit, and wherein said detected positional data are assigned to body structure data, in order to jointly use said body structure data in assignment with said positional data, within the context of assisting the treatment, wherein body structure data is used that is obtained based on a generic model that has been adapted by linking it with patient-characteristic detection data.
US 2005/0004451 A1 discloses a method for computer-assisted medical navigation or pre-operative treatment planning, wherein a position of a patient or a part of a patient's body is detected; positions of medical treatment devices or treatment-assisting devices are detected; and the detected positions are assigned to body structure data, said body structure data being obtained form a three-dimensional generic model.
WO 01/22368 A1 discloses a method and a system for three-dimensional reconstruction of an image representing the surface contours of an object from a two-dimensional view of said object obtained by X-ray, which consists of: determining the position of the photographing source in a reference repository; selecting a predefined model constituting a mean form of the object, and repeating the process until the contours of the model are such that the variations between the overhead projection rays of the contours of the two-dimensional image from the source and the model surface are minimal; selecting an orientation and a position for the model in the reference repository; and then selecting a deformation of the model to modify its contours in three dimensions.
US 2005/0008219 A1 discloses a radiographic imaging method for three-dimensional reconstruction in which the three-dimensional shape of a model representing an object is calculated from a geometrical model of the object that is known a priori, and obtained from a confinement volume of the object estimated from a geometrical pattern visible in two images and from knowledge of the positions of the sources. A geometrical model can be used that comprises information that enables use of an estimator to establish a geometrical characteristic for the model representing the object.